Conference Agenda

As temperature is expected to continue to raise due to climate change, research on the effect of extremely hot weather on socioeconomic wellbeing is becoming increasingly important. In this paper, using a large student-level panel data, we investigate the effect of extreme temperatures on standardized-test scores of children between 11 to 15 years old who live in disadvantaged households. Our results show that exposure to an increase of 1°C leads to a 0.07 and 0.085 standard deviation decrease in the Spanish and mathematics test scores, respectively. Also, an increase of one standard deviation (0.93°C) in the long-term temperature average is associated with a 0.04 and a 0.03 standard deviation decrease in those scores. The results are dependent on the historical mean temperature of the school’s municipality: students in cold municipalities benefit from hotter days.

Our goals are four: (i) Determine whether the effects of temperature variations on mortality are different between occupation groups. (ii) Explore whether these het- erogeneous effects persist after accounting for observed socioeconomic differences. (iii) Propose a simple theoretical framework for policymakers to understand the ef- fects of public policies on the impacts of temperature deviations on worker mortality. (iv) Analyze the effects of two policies on the relationship between temperature and mortality across occupations; access to social security, and minimum wage increases. We show that the effects of temperature are heterogeneous between occupations. Primary sector workers are particularly affected. These differences persist even after controlling for a relevant set of sociodemographic characteristics between occupa- tions. The introduction of universal social security and the increase in minimum wages decreased mortality rates for all labor groups.

We investigate the impact of climate change on firms’ investment in research

and development (R&D) in developing countries. The paper relies on two contrasting hypotheses. In the first hypothesis, we speculate an optimistic situation

where climate change could induce firms to spend on R&D to both reduce their

environmental impact and curb the effects of future climate shocks. In the second

hypothesis, we propose a pessimistic scenario where climate change would reduce

firms’ incentives to invest in R&D. This second hypothesis would mainly be due

to tighter conditions for access to finance from lenders, given the increased uncertainty about the firm’s future returns in the face of climate change. The empirical

results support the second scenario, small firms being more severely affected. Furthermore, we examine the underlying mechanisms and identify financial access as

the key channel through which climate change reduces R&D investment.

Global food systems are a major contributor to greenhouse gas emissions, yet strategies to mitigate food-related emissions receive low public acceptance. To better understand this gap, this study pioneers a comprehensive analysis of household-level food carbon footprints using a representative panel survey for France from 2017-2019. Using machine learning techniques to match food purchases and environmental data, I unveil significant emission disparities across sociodemographic groups, with a notable portion of these differences attributable to unobserved heterogeneity. By segmenting households into quartiles based on their current emission levels, I estimate a structural demand model that reveals distinct profiles in consumption behavior and price sensitivity, particularly contrasting low and high-emission households. These findings underscore the need to consider households' heterogeneous reactions to price changes when designing climate-related food policies.